Founding Data & AI Engineer

Sierra Studio is a performance creative agency that specializes in creating ads for platforms like TikTok and Meta. They are seeking a Founding Data & AI Engineer to build the foundational data systems for their new Creative Engine, focusing on data pipelines, LLM workflows, and integrating AI-driven insights for creative strategies.

Responsibilities:

• Design the data foundation: pipelines that pull, store, and structure performance, sales, and engagement data across hundreds of client accounts (performance creative, TikTok Shop, TikTok LIVE, and Meta), handling the messiness of real platform APIs
• Build the LLM analysis layer, using Gemini to watch and tag every video and Claude for generation, with structured output at scale and sane cost controls
• Build search and discovery with semantic search via pgvector, so a strategist can ask "what are the top hooks for beauty this week?" and get a real answer, not a keyword dump
• Build the "brain": connect viral organic references, top-performing ads, content tags, and creator history into queryable creative intelligence, accessible through the web app, Slack, and Cowork
• Develop creator-performance matching, linking creator history, content tags, and ad metrics to sharpen casting decisions
• Own the full stack on top of your data work: dashboards, tag browsers, enrichment queues, and export tools in Django + HTMX + Tailwind, moving fast with Claude Code (no dedicated frontend hire required)
• Integrate external APIs (TikTok, Meta, Motion, Cruva) and internal async pipelines (Celery + Redis)

Requirements:

• 5+ years building production, data-heavy applications with Python/Django and PostgreSQL (senior / lead level, autonomous, low-process)
• Strong SQL well beyond basic ORM queries (aggregations, joins, window functions) and comfort designing schemas and data models straight from use cases
• Experience designing and debugging async data pipelines (Celery + Redis or equivalent)
• Genuinely LLM-fluent: hands-on with LLM APIs in production, prompt engineering, structured output, and cost management
• Fluent with agentic coding tools (Claude Code, Cowork) and excited to use them to move fast, including building full-stack on top of your own data work
• Experience integrating messy third-party APIs (rate limits, auth flows, inconsistent data)
• Comfortable owning frontend (Django templates + HTMX + Tailwind) with AI assistance — you ship the whole feature, you just don't need to be a frontend expert
• Strong written communication and high ownership on a small, async team
• An AI engineer at heart — you've built agent harnesses, RAG, or LLM eval pipelines (even side projects count)
• Background in or curiosity about ML fundamentals, like knowing when a simple scoring function beats a complex model
• Experience with video or audio processing pipelines
• Domain experience in ad tech, creator economy, performance marketing, or marketplace platforms
• Have worked with a US-based team before — async, English-fluent, knows the drill